import json
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import datetime

import seaborn
seaborn.set_theme()

pd.set_option('future.no_silent_downcasting', True)

with open('regions-m49.json') as f:
    regions = json.load(f)['regions']
    regions = {v: n for n, v in regions.items()}

with open('countries-m49.json') as f:
    countries = json.load(f)['countries']
    country_subregions = {c['name']: regions[c['subRegion']] for c in countries}
    country_regions = {c['name']: regions[c['region']] for c in countries}

country_mapping = {
    'Czech Republic': 'Czechia',
    'Iran': 'Iran (Islamic Republic of)',
    'Russia': 'Russian Federation',
    'South Korea': 'Republic of Korea',
    'Taiwan': 'China',  # UN is an abomination
    'Turkey': 'T\u00fcrkiye',
    'United Kingdom': 'United Kingdom of Great Britain and Northern Ireland',
    'United States': 'United States of America',
}

max_year = 2023
years = range(1954, max_year + 1)
max_date = pd.to_datetime(datetime.date(year = max_year + 1, month = 1, day = 1))

copyright_text = 'CC BY-SA 4.0 Andrey Upadyshev (image) and\nWikipedia, List of commercial nuclear reactors (data)'
copyright_font_size = 10

def format_years_ticks(ax):
    for label in ax.get_xticklabels():
        if label.get_text() in ('1957', '1979', '1986', '2011'):
            label.set_color('red')


def format_number_plants_ticks(ax, ymin, ymax):
    def fmt(val, pos):
        return int(abs(val))
    ax.yaxis.set_major_formatter(fmt)
    ax.set_ylim(-ymin, ymax)

orig_input_df = pd.read_csv('./reactors.csv').convert_dtypes()
for col in ('Begin building', 'Commercial operation', 'Closed'):
    orig_input_df[f'{col} date'] = pd.to_datetime(orig_input_df[col])
    orig_input_df[f'{col}'] = orig_input_df[f'{col} date'].dt.year

input_df = orig_input_df[orig_input_df['Begin building'].notna() & (orig_input_df['Begin building'] <= max_year)].reset_index(drop=True)
input_df.loc[input_df['Commercial operation'] > max_year, 'Commercial operation'] = None
input_df.loc[input_df['Closed'] > max_year, 'Closed'] = None

input_df['SubRegion'] = input_df['Country'].map(lambda x: country_subregions[country_mapping.get(x, x)])
input_df['Region'] = input_df['Country'].map(lambda x: country_regions[country_mapping.get(x, x)])
input_df['Operated closed'] = input_df['Closed'].where(input_df['Commercial operation'].notna(), None)
input_df['Construction time'] = (input_df['Commercial operation date'] - input_df['Begin building date']).dt.total_seconds() / (365.25 * 24 * 60 * 60)
input_df

	Country	Plant name	Unit No.	Type	Model	Status	Capacity (MW)	Begin building	Commercial operation	Closed	Begin building date	Commercial operation date	Closed date	SubRegion	Region	Operated closed	Construction time
0	Argentina	Atucha	1	PHWR	Siemens-KWU	Operational	335.0	1968.0	1974.0	NaN	1968-06-01	1974-06-24	NaT	Latin America and the Caribbean	Americas	NaN	6.061602
1	Argentina	Atucha	2	PHWR	Siemens-KWU	Operational	692.0	1981.0	2014.0	NaN	1981-07-14	2014-06-27	NaT	Latin America and the Caribbean	Americas	NaN	32.952772
2	Argentina	Embalse	1	PHWR	CANDU-6	Operational	600.0	1974.0	1984.0	NaN	1974-04-01	1984-01-20	NaT	Latin America and the Caribbean	Americas	NaN	9.804244
3	Argentina	CAREM	1	PWR	CAREM25	Under construction	25.0	2014.0	NaN	NaN	2014-02-08	NaT	NaT	Latin America and the Caribbean	Americas	NaN	NaN
4	Armenia	Metsamor	1	PWR	VVER-440/V-270	Shut down	376.0	1969.0	1977.0	1989.0	1969-07-01	1977-10-06	1989-02-25	Western Asia	Asia	1989.0	8.265572
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
746	United States	Watts Bar	2	PWR	WH 4-Loop (ICECOND)	Operational	1164.0	1973.0	2016.0	NaN	1973-09-01	2016-06-04	NaT	Northern America	Americas	NaN	42.757016
747	United States	Wolf Creek	1	PWR	WH 4-Loop (DRY)	Operational	1200.0	1977.0	1985.0	NaN	1977-05-31	1985-09-03	NaT	Northern America	Americas	NaN	8.260096
748	United States	Yankee Rowe	1	PWR	WH (DRY)	Dismantled	167.0	1957.0	1961.0	1991.0	1957-11-01	1961-07-01	1991-10-01	Northern America	Americas	1991.0	3.663244
749	United States	Zion	1	PWR	WH (DRY)	Dismantled	1040.0	1968.0	1973.0	1998.0	1968-12-01	1973-12-31	1998-02-13	Northern America	Americas	1998.0	5.081451
750	United States	Zion	2	PWR	WH (DRY)	Dismantled	1040.0	1968.0	1974.0	1998.0	1968-12-01	1974-09-17	1998-02-13	Northern America	Americas	1998.0	5.793292

751 rows × 17 columns

total_constructed_by_subregion = input_df.groupby(['SubRegion', 'Region'])[['Begin building', 'Commercial operation', 'Closed']].count().reset_index().sort_values('Begin building', ascending=False).reset_index(drop=True)
total_constructed_by_subregion

	SubRegion	Region	Begin building	Commercial operation	Closed
0	Eastern Asia	Asia	181	147	34
1	Northern America	Americas	165	159	52
2	Western Europe	Europe	125	120	58
3	Eastern Europe	Europe	122	94	29
4	Northern Europe	Europe	67	64	45
5	Southern Asia	Asia	42	31	2
6	Southern Europe	Europe	21	15	13
7	Latin America and the Caribbean	Americas	11	7	2
8	Western Asia	Asia	10	5	1
9	Northern Africa	Africa	3	0	0
10	Sub-Saharan Africa	Africa	2	2	0
11	Central Asia	Asia	1	1	1
12	South-eastern Asia	Asia	1	0	1

total_constructed_by_country = input_df.groupby(['Country', 'SubRegion', 'Region'])[['Begin building', 'Commercial operation', 'Closed']].count().reset_index().sort_values('Begin building', ascending=False).reset_index(drop=True)
total_constructed_by_country

	Country	SubRegion	Region	Begin building	Commercial operation	Closed
0	United States	Northern America	Americas	140	134	46
1	China	Eastern Asia	Asia	81	55	0
2	France	Western Europe	Europe	69	68	12
3	Japan	Eastern Asia	Asia	62	59	26
4	Russia	Eastern Europe	Europe	62	47	10
5	United Kingdom	Northern Europe	Europe	46	44	35
6	Germany	Western Europe	Europe	39	36	39
7	India	Southern Asia	Asia	31	23	1
8	South Korea	Eastern Asia	Asia	30	27	2
9	Canada	Northern America	Americas	25	25	6
10	Ukraine	Eastern Europe	Europe	25	19	8
11	Sweden	Northern Europe	Europe	14	13	8
12	Spain	Southern Europe	Europe	14	10	7
13	Slovakia	Eastern Europe	Europe	9	8	3
14	Belgium	Western Europe	Europe	8	8	3
15	Bulgaria	Eastern Europe	Europe	8	6	4
16	Taiwan	Eastern Asia	Asia	8	6	6
17	Pakistan	Southern Asia	Asia	7	7	1
18	Italy	Southern Europe	Europe	6	4	6
19	Switzerland	Western Europe	Europe	6	6	2
20	Czech Republic	Eastern Europe	Europe	6	6	0
21	Finland	Northern Europe	Europe	5	5	0
22	Turkey	Western Asia	Asia	4	0	0
23	United Arab Emirates	Western Asia	Asia	4	3	0
24	Argentina	Latin America and the Caribbean	Americas	4	3	0
25	Belarus	Eastern Europe	Europe	4	2	2
26	Hungary	Eastern Europe	Europe	4	4	0
27	Brazil	Latin America and the Caribbean	Americas	3	2	0
28	Egypt	Northern Africa	Africa	3	0	0
29	Netherlands	Western Europe	Europe	2	2	1
30	Armenia	Western Asia	Asia	2	2	1
31	Bangladesh	Southern Asia	Asia	2	0	0
32	Cuba	Latin America and the Caribbean	Americas	2	0	2
33	Iran	Southern Asia	Asia	2	1	0
34	South Africa	Sub-Saharan Africa	Africa	2	2	0
35	Lithuania	Northern Europe	Europe	2	2	2
36	Mexico	Latin America and the Caribbean	Americas	2	2	0
37	Romania	Eastern Europe	Europe	2	2	0
38	Poland	Eastern Europe	Europe	2	0	2
39	Philippines	South-eastern Asia	Asia	1	0	1
40	Slovenia	Southern Europe	Europe	1	1	0
41	Austria	Western Europe	Europe	1	0	1
42	Kazakhstan	Central Asia	Asia	1	1	1

Construction time

construction_time = input_df.groupby(['Begin building'])['Construction time'].agg(['min', 'median', 'max']).reindex(years, fill_value=0)

fig, ax = plt.subplots(figsize=(11, 5))

construction_time.plot.bar(ax=ax, width=0.8)

ax.set_title('Years of construction time by the year when construction started - World')
ax.set_xlabel(None)
format_years_ticks(ax)
ax.yaxis.set_major_formatter(lambda val, pos: int(val))
ax.yaxis.set_major_locator(ticker.MultipleLocator(5))
ax.text(0, ax.get_ylim()[1] - 0.1, copyright_text, fontsize=copyright_font_size, verticalalignment='top')
ax.legend()

fig.tight_layout()

top_countries = total_constructed_by_country['Country'].to_list()
construction_time = input_df.groupby(['Country', 'Begin building'])['Construction time'].agg(['min', 'median', 'max'])
ymax = construction_time.max(axis=None) + 1

for c in top_countries:
    df = construction_time[construction_time.index.get_level_values(0) == c].droplevel(0).reindex(years, fill_value=0)
    
    fig, ax = plt.subplots(figsize=(11, 5))

    df.plot.bar(ax=ax, width=0.8)

    ax.set_title(f'Years of construction time by the year when construction started - {c}')
    ax.set_xlabel(None)
    format_years_ticks(ax)

    ax.yaxis.set_major_formatter(lambda val, pos: int(abs(val)))
    ax.yaxis.set_major_locator(ticker.MultipleLocator(5))

    ax.set_ylim(0, ymax)
    ax.text(0, ax.get_ylim()[1], copyright_text, fontsize=copyright_font_size, verticalalignment='top')
    ax.legend()

    fig.tight_layout()

/var/folders/2z/kr9wj6s90nn6nkdsddywzyfw0000gn/T/ipykernel_34796/1224979684.py:8: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`). Consider using `matplotlib.pyplot.close()`.
  fig, ax = plt.subplots(figsize=(11, 5))

Number of constructed and operated reactors

World stats

num_building_started = input_df.groupby(['Begin building'])['Begin building'].count()
num_connected = input_df.groupby(['Commercial operation'])['Commercial operation'].count()
num_closed = input_df.groupby(['Closed'])['Closed'].count()
num_operated_closed = input_df.groupby(['Operated closed'])['Operated closed'].count()

max_building_started = num_building_started.max()
max_num_closed = num_closed.max()
ymax = (max_building_started + 4) // 5 * 5
ymin = (max_num_closed + 4) // 5 * 5

combined = pd.concat([
        num_building_started,
        num_connected,
        num_closed,
        num_operated_closed,
    ], axis=1)

combined = combined.reindex(years, fill_value=0)

combined['Commercial operation tot'] = combined['Commercial operation'].fillna(0).cumsum()
combined['Operated closed tot'] = combined['Operated closed'].fillna(0).cumsum()
combined['In operation'] = combined['Commercial operation tot'] - combined['Operated closed tot']

fig, ax = plt.subplots(2, 1, figsize=(11, 10))

ax1, ax2 = ax

combined['Begin building'].plot.bar(ax=ax1, label='Construction started')
(-combined['Closed']).plot.bar(ax=ax1, color='red', label='Closed')

ax1.set_title('World')
ax1.set_xlabel(None)
format_years_ticks(ax1)
format_number_plants_ticks(ax1, ymin, ymax)
ax1.text(0, -ymin, copyright_text, fontsize=copyright_font_size, verticalalignment='bottom')
ax1.legend()

combined['In operation'].plot.bar(ax=ax2, label='Number in operation')
combined['Commercial operation'].plot.bar(ax=ax2, color='black', label='Operation started')
format_years_ticks(ax2)
#ax2.text(0, ax2.get_ylim()[1], copyright_text, fontsize=copyright_font_size, verticalalignment='top')
ax2.legend()

fig.tight_layout()

Region stats

total_constructed_by_region = input_df.groupby(['Region'])[['Begin building', 'Commercial operation', 'Closed']].count().reset_index().sort_values('Begin building', ascending=False).reset_index(drop=True)

num_building_started = input_df.groupby(['Region', 'Begin building'])['Begin building'].count()
num_connected = input_df.groupby(['Region', 'Commercial operation'])['Commercial operation'].count()
num_closed = input_df.groupby(['Region', 'Closed'])['Closed'].count()
num_operated_closed = input_df.groupby(['Region', 'Operated closed'])['Operated closed'].count()

#top_regions = total_constructed_by_region[total_constructed_by_region['Begin building'] > 10]['Region'].to_list()
top_regions = total_constructed_by_region['Region'].to_list()

regions = sorted(c for c in input_df['Region'].unique() if c in num_building_started)

max_building_started = num_building_started.max()
max_num_closed = num_closed.max()
ymax = (max_building_started + 4) // 5 * 5
ymin = (max_num_closed + 4) // 5 * 5
tot_ymax_regions = 250  # TODO: calculate from data


for c in top_regions:
    combined = pd.concat([
        num_building_started[c],
        num_connected[c] if c in num_connected else pd.DataFrame(columns=['Commercial operation']),
        num_closed[c] if c in num_closed else pd.DataFrame(columns=['Closed']),
        num_operated_closed[c] if c in num_operated_closed else pd.DataFrame(columns=['Operated closed']),
    ], axis=1)
    
    combined = combined.reindex(years, fill_value=0)

    combined['Commercial operation tot'] = combined['Commercial operation'].fillna(0).cumsum()
    combined['Operated closed tot'] = combined['Operated closed'].fillna(0).cumsum()
    combined['In operation'] = combined['Commercial operation tot'] - combined['Operated closed tot']

    fig, ax = plt.subplots(2, 1, figsize=(11, 10))

    ax1, ax2 = ax

    combined['Begin building'].plot.bar(ax=ax1, label='Construction started')
    (-combined['Closed']).plot.bar(ax=ax1, color='red', label='Closed')

    ax1.set_title(f'{c} (UN M49)')
    ax1.set_xlabel(None)
    format_years_ticks(ax1)
    format_number_plants_ticks(ax1, ymin, ymax)
    ax1.text(0, -ymin, copyright_text, fontsize=copyright_font_size, verticalalignment='bottom')
    ax1.legend()

    combined['In operation'].plot.bar(ax=ax2, label='Number in operation')
    combined['Commercial operation'].plot.bar(ax=ax2, color='black', label='Operation started')
    format_years_ticks(ax2)
    ax2.set_ylim(0, tot_ymax_regions)
    #ax2.text(0, ax2.get_ylim()[1], copyright_text, fontsize=copyright_font_size, verticalalignment='top')
    ax2.legend()


    fig.tight_layout()

europe_df = input_df[(input_df['Region'] == 'Europe') & (input_df['SubRegion'] != 'Eastern Europe') & (input_df['SubRegion'] != 'Lithuania')]
num_building_started = europe_df.groupby(['Begin building'])['Begin building'].count()
num_connected = europe_df.groupby(['Commercial operation'])['Commercial operation'].count()
num_closed = europe_df.groupby(['Closed'])['Closed'].count()
num_operated_closed = europe_df.groupby(['Operated closed'])['Operated closed'].count()

max_building_started = num_building_started.max()
max_num_closed = num_closed.max()
ymax = (max_building_started + 4) // 5 * 5
ymin = (max_num_closed + 4) // 5 * 5

combined = pd.concat([
        num_building_started,
        num_connected,
        num_closed,
        num_operated_closed,
    ], axis=1)

combined = combined.reindex(years, fill_value=0)

combined['Commercial operation tot'] = combined['Commercial operation'].fillna(0).cumsum()
combined['Operated closed tot'] = combined['Operated closed'].fillna(0).cumsum()
combined['In operation'] = combined['Commercial operation tot'] - combined['Operated closed tot']

fig, ax = plt.subplots(2, 1, figsize=(11, 10))

ax1, ax2 = ax

combined['Begin building'].plot.bar(ax=ax1, label='Construction started')
(-combined['Closed']).plot.bar(ax=ax1, color='red', label='Closed')

ax1.set_title('Europe excluding Eastern Europe and ex-USSR countries')
ax1.set_xlabel(None)
format_years_ticks(ax1)
format_number_plants_ticks(ax1, ymin, ymax)
ax1.text(0, -ymin, copyright_text, fontsize=copyright_font_size, verticalalignment='bottom')
ax1.legend()

combined['In operation'].plot.bar(ax=ax2, label='Number in operation')
combined['Commercial operation'].plot.bar(ax=ax2, color='black', label='Operation started')
format_years_ticks(ax2)
ax2.set_ylim(0, tot_ymax_regions)
#ax2.text(0, ax2.get_ylim()[1], copyright_text, fontsize=copyright_font_size, verticalalignment='top')
ax2.legend()

fig.tight_layout()

Subregion stats

num_building_started = input_df.groupby(['SubRegion', 'Begin building'])['Begin building'].count()
num_connected = input_df.groupby(['SubRegion', 'Commercial operation'])['Commercial operation'].count()
num_closed = input_df.groupby(['SubRegion', 'Closed'])['Closed'].count()
num_operated_closed = input_df.groupby(['SubRegion', 'Operated closed'])['Operated closed'].count()

sub_regions = sorted(c for c in input_df['SubRegion'].unique() if c in num_building_started)
#top_regions = total_constructed_by_subregion[total_constructed_by_subregion['Begin building'] > 10]['SubRegion'].to_list()
top_regions = total_constructed_by_subregion['SubRegion'].to_list()

max_building_started = num_building_started.max()
max_num_closed = num_closed.max()
ymax = (max_building_started + 4) // 5 * 5
ymin = (max_num_closed + 4) // 5 * 5


for c in top_regions:
    combined = pd.concat([
        num_building_started[c],
        num_connected[c] if c in num_connected else pd.DataFrame(columns=['Commercial operation']),
        num_closed[c] if c in num_closed else pd.DataFrame(columns=['Closed']),
        num_operated_closed[c] if c in num_operated_closed else pd.DataFrame(columns=['Operated closed']),
    ], axis=1)
    
    combined = combined.reindex(years, fill_value=0)

    combined['Commercial operation tot'] = combined['Commercial operation'].fillna(0).cumsum()
    combined['Operated closed tot'] = combined['Operated closed'].fillna(0).cumsum()
    combined['In operation'] = combined['Commercial operation tot'] - combined['Operated closed tot']

    fig, ax = plt.subplots(2, 1, figsize=(11, 10))

    ax1, ax2 = ax

    combined['Begin building'].plot.bar(ax=ax1, label='Construction started')
    (-combined['Closed']).plot.bar(ax=ax1, color='red', label='Closed')

    ax1.set_title(f'{c} (UN M49)')
    ax1.set_xlabel(None)
    format_years_ticks(ax1)
    format_number_plants_ticks(ax1, ymin, ymax)
    ax1.text(0, -ymin, copyright_text, fontsize=copyright_font_size, verticalalignment='bottom')
    ax1.legend()

    combined['In operation'].plot.bar(ax=ax2, label='Number in operation')
    combined['Commercial operation'].plot.bar(ax=ax2, color='black', label='Operation started')
    format_years_ticks(ax2)
    ax2.set_ylim(0, tot_ymax_regions)
    #ax2.text(0, ax2.get_ylim()[1], copyright_text, fontsize=copyright_font_size, verticalalignment='top')
    ax2.legend()


    fig.tight_layout()

Country stats

num_building_started = input_df.groupby(['Country', 'Begin building'])['Begin building'].count()
num_connected = input_df.groupby(['Country', 'Commercial operation'])['Commercial operation'].count()
num_closed = input_df.groupby(['Country', 'Closed'])['Closed'].count()
num_operated_closed = input_df.groupby(['Country', 'Operated closed'])['Operated closed'].count()

countries = sorted(c for c in input_df['Country'].unique() if c in num_building_started)
#top_countries = total_constructed_by_country[total_constructed_by_country['Begin building'] >= 10]['Country'].to_list()
top_countries = total_constructed_by_country['Country'].to_list()

max_building_started = num_building_started.max()
max_num_closed = num_closed.max()
ymax = (max_building_started + 4) // 5 * 5
ymin = (max_num_closed + 4) // 5 * 5
tot_ymax = 120  # TODO: calculate from data


for c in top_countries:
    combined = pd.concat([
        num_building_started[c],
        num_connected[c] if c in num_connected else pd.DataFrame(columns=['Commercial operation']),
        num_closed[c] if c in num_closed else pd.DataFrame(columns=['Closed']),
        num_operated_closed[c] if c in num_operated_closed else pd.DataFrame(columns=['Operated closed']),
    ], axis=1)
    
    combined = combined.reindex(years, fill_value=0)

    combined['Commercial operation tot'] = combined['Commercial operation'].fillna(0).cumsum()
    combined['Operated closed tot'] = combined['Operated closed'].fillna(0).cumsum()
    combined['In operation'] = combined['Commercial operation tot'] - combined['Operated closed tot']

    fig, ax = plt.subplots(2, 1, figsize=(11, 10))

    ax1, ax2 = ax

    combined['Begin building'].plot.bar(ax=ax1, label='Construction started')
    (-combined['Closed']).plot.bar(ax=ax1, color='red', label='Closed')

    ax1.set_title(c)
    ax1.set_xlabel(None)
    format_years_ticks(ax1)
    format_number_plants_ticks(ax1, ymin, ymax)
    ax1.text(0, -ymin, copyright_text, fontsize=copyright_font_size, verticalalignment='bottom')
    ax1.legend()

    combined['In operation'].plot.bar(ax=ax2, label='Number in operation')
    combined['Commercial operation'].plot.bar(ax=ax2, color='black', label='Operation started')
    format_years_ticks(ax2)
    ax2.set_ylim(0, tot_ymax)
    #ax2.text(0, ax2.get_ylim()[1], copyright_text, fontsize=copyright_font_size, verticalalignment='top')
    ax2.legend()

    fig.tight_layout()

/var/folders/2z/kr9wj6s90nn6nkdsddywzyfw0000gn/T/ipykernel_34796/3530068090.py:31: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`). Consider using `matplotlib.pyplot.close()`.
  fig, ax = plt.subplots(2, 1, figsize=(11, 10))

Never opened reactors

# Never opened
never_opened_df = input_df[input_df['Commercial operation'].isna() & input_df['Begin building'].notna() & input_df['Closed'].notna()].sort_values('Closed')

num_building_started = never_opened_df.groupby(['Begin building'])['Begin building'].count()
num_closed = never_opened_df.groupby(['Closed'])['Closed'].count()

combined = pd.concat([
        num_building_started,
        num_closed,
    ], axis=1)

combined = combined.reindex(years, fill_value=0)

fig, ax = plt.subplots(figsize=(11, 5))

combined['Begin building'].plot.bar(ax=ax, label='Construction started')
(-combined['Closed']).plot.bar(ax=ax, color='red', label='Closed')

ax.set_title('Never operated reactors')
ax.set_xlabel(None)
format_years_ticks(ax)
ax.yaxis.set_major_formatter(lambda val, pos: int(val))
ax.text(0, ax.get_ylim()[0], copyright_text, fontsize=copyright_font_size, verticalalignment='bottom')
ax.legend()

fig.tight_layout()

never_opened_df.groupby(['Country', 'Closed'])['Closed'].count().sort_values(ascending=False)

Country        Closed
Spain          1984.0    4
United States  1984.0    3
Belarus        1987.0    2
Cuba           1992.0    2
Germany        1990.0    2
Italy          1988.0    2
Poland         1990.0    2
Taiwan         2014.0    2
Ukraine        1987.0    2
               1990.0    2
United States  1983.0    2
Austria        1978.0    1
Germany        1985.0    1
Philippines    1986.0    1
Sweden         1970.0    1
Name: Closed, dtype: int64

never_opened_df.groupby(['Country', 'Begin building'])['Begin building'].count().sort_values(ascending=False)

Country        Begin building
United States  1975.0            4
Poland         1982.0            2
Ukraine        1988.0            2
               1984.0            2
Germany        1983.0            2
Italy          1982.0            2
Taiwan         1999.0            2
Belarus        1983.0            2
Spain          1972.0            2
               1975.0            2
Sweden         1965.0            1
Austria        1972.0            1
Philippines    1976.0            1
Germany        1972.0            1
Cuba           1985.0            1
               1983.0            1
United States  1977.0            1
Name: Begin building, dtype: int64